Title: New Paradigm for International Insurance Comparison: With an Application to Comparison of Seven Insu
1New Paradigm for International Insurance
ComparisonWith an Application to Comparison of
Seven Insurance Markets
- Wei Zheng, Peking University
- Yongdong Liu, China Academy of Sciences
- Yiting Deng, Peking University
2Outline
- 1. Introduction
- 2. Comparison of Insurance Growth Level
- 3. Comparison of Insurance Growth Structure
- 4. Economic and Institutional Factors in
Insurance Growth - 5. Conclusion
31. Introduction
- Commonly used methods for international insurance
comparison - premium income method
- insurance density method
- insurance penetration method
- Limitations of the above methods
- They fail to take into consideration the
relationship between insurance penetration and
economic development stage - A new paradigm is proposed
- BRIP comparison of Insurance Growth Level
- Trichotomy comparison of Insurance Growth
Structure
41. Introduction
- Application to seven markets
- U.S.
- Japan
- U.K.
- Brazil
- Russia
- India
- China
- Sometimes we also refer to data of OECD average,
BRIC average and world average.
52. Comparison of Insurance Growth Level
- 2.1 New Method BRIP
- 2.2 Ordinary model of insurance growth
- 2.3 Comparison of Ranking Results under the New
Method and the Traditional Methods
62.1 New Method BRIP
- Benchmark Ratio of Insurance Penetration
- benchmark penetration refers to the world
average insurance penetration at a countrys
economic level - actual penetration refers to a countrys actual
penetration - The central idea here is to measure the
benchmark-adjusted insurance growth level
instead of a traditional one. - The difficulty is how to get the benchmark
penetration.
72.2 Ordinary model of insurance growth
- Carter Dickinson (1992) and Enz (2000)
developed a logistic model to depict the
relationship between insurance penetration and
GDP per capita. - Y insurance penetration
- X GDP per capita
- C1, C2, C3 three parameters
- e residual
- This paper uses the data of 95 countries
(regions) over the past 27 years (1980-2006) as
the sample.
8Estimates of Ordinary Growth Model
The Robust t-statistics is in parentheses. The
term of means the level of significance is
1.
9Regression Curves of Ordinary Growth Model
10Why use BRIP ?
- The international insurance comparison will make
more sense only when it is based on the
comparable benchmark-adjusted insurance growth
level. - BRIP is such a benchmark adjustment to
insurance penetration. - So, BRIP represents a more reasonable indicator
for the international insurance comparison.
11Whats the economic implications of BRIP ?
- BRIP 1 the countrys actual penetration is
equal to the world average penetration at that
countrys economic development stage - BRIP lt 1 the actual penetration is less than the
average - BRIP gt 1 the actual penetration is greater than
the average - There is a positive correlation between the BRIP
and the relative insurance growth level of that
country.
122.3 Comparison of Ranking Results (2006)
13To sum it up,
- We should have a new recognition for the
insurance growth level of each country - the benchmark-adjusted insurance growth level of
the emerging countries is not as low as what
traditional methods indicate - the benchmark-adjusted insurance growth level of
the developed countries is not as high as what
traditional methods imply - Put it in another way, for the year 2006, the
ranking of the growth potential of the seven
countries would be like this (from large to
small) Russia, Brazil, China, US, Japan, India
and UK
143. Comparison of Insurance Growth Structure
- 3.1 Introduction to Trichotomy
- 3.2 Adjusted model of insurance growth
- 3.3 Comparison of Growth Structure
153.1 Introduction to Trichotomy
- Insurance growth can be decomposed into three
parts - Regular growth
- Insurance growth accompanying the economic growth
assuming the insurance penetration is unchanged - Deepening growth
- Insurance growth brought about by the increase of
insurance penetration induced by economic growth - Institutional growth
- The remaining part of the growth, which is
brought about by the institutional factors after
the economic factors have been deducted
16Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
17Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
18Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
193.2 Adjusted model of insurance growth
- Y insurance penetration
- X GDP per capita
- C1, C2, and C3 three parameters
- Di(i1,94) country dummy with respect to
country i - ?i(i1,94) coefficient for Di
- e residual
20Estimates of Adjusted Growth Model
The Robust t-statistics is in parentheses. The
term of means the level of significance is
1.
21Regression Curves of Adjusted Growth Model
223.3 Comparison of Growth Structure
23To sum it up,
- In developed countries, the insurance growth is
mainly driven by the economic factors (including
regular and deepening factors) - In emerging countries, the insurance growth is
largely driven by the institutional factors
244. Economic and Institutional Factors in
Insurance Growth
- 4.1 Comparison of Two Growth Models
- 4.2 Discussion on Institutional Factors
- 4.3 Discussion on Developed and Emerging Countries
254.1 Comparison of Two Growth Models
- Ordinary growth model
- combines both the economic factors and
institutional factors that influence the
insurance growth - Adjusted growth model
- separates the country-specific institutional
influences and the common economic influences
26Comparison of Two Models for Life Insurance
27Comparison of Two Models for Non-Life Insurance
28Comparison of Two Models for Insurance Industry
29Comparison of Two Models for Insurance Industry
- In the figure
- Ordinary growth curve combines both economic and
institutional factors - Adjusted growth curve reflects only pure
economic factors - When GDP per capita is low, the ordinary curve is
higher than the adjusted curve, which indicates
that institutional factors facilitate the growth
of the insurance industry to some degree. - When GDP per capita is high, the ordinary curve
is obviously lower than the adjusted curve, which
indicates that institutional factors markedly
restrain the growth of the insurance industry.
304.2 Discussion on Institutional Factors
- Major institutions
- social security system (systematic institution)
- dominantly affects the life insurance
- legal system (systematic institution)
- dominantly affects the non-life insurance, with
its most typical components being the compulsory
insurance and liability insurance - culture (non-systematic institution)
- religion (non-systematic institution)
31Effects of institutional factors on life insurance
- Relationship between life insurance and social
security - usually substitutable
- the better developed the social security system
is, the more the life insurance growth is
restricted - Relationship between social security and GDP per
capita - usually positive correlation
- low GDP per capita countries social security
system is usually under-developed - high GDP per capita countries social security
system is usually well-developed - Thus, as the GDP per capita increases (with the
improvement of social security system), the
negative effects of institutional factors on life
insurance would gradually increase.
32Effects of institutional factors on non-life
insurance
- Relationship between non-life insurance and
certain legal policies - usually complementary
- the more compulsory insurance and liability
insurance are implemented, the more growth
opportunities will be created for the non-life
insurance - Relationship between certain legal policies and
GDP per capita - usually no direct relation
- the governments decision of whether to adopt
those legal policies (the compulsory insurance
and liability insurance) is mainly based on the
consideration of social policy (such as equity
and justice), and generally is not related to GDP
per capita - Thus, no matter how large GDP per capita is,
institutional factors will always bring positive
effects to the growth of non-life insurance.
33Effects of institutional factors on insurance
industry
- When GDP per capita is low
- institutions have some positive effects on both
the life insurance and the non-life insurance - with its net effects on the insurance industry
being positive - When GDP per capita is high
- institutions have remarkably negative effects on
the life insurance and some positive effects on
the non-life insurance - with its net effects on the insurance industry
being negative, and the negative effects are
notable
344.3 Discussion on Developed and Emerging Countries
- For the emerging countries
- institutional factors facilitate the growth of
the insurance industry to some degree - For the developed countries
- institutional factors notably restrain the growth
of the insurance industry - It could also imply that as the economy develops,
the contribution of the institutional factors to
the insurance growth would gradually decrease,
and the economic factors would play a more active
role in driving the insurance growth.
354.3 Discussion on Developed and Emerging Countries
- This implication suggests that, for those
emerging countries, after the insurance industry
having experienced a period of taking-off, its
growth will gradually change from being driven
by both economic and institutional factors to
being driven mainly by economic factors. - Following this judgment, it is extremely
important for the insurance industry in the
emerging countries to upgrade its growth strategy
from the extensive developing pattern to a
refined and sustainable developing pattern, for
the former one will lose its foundation for
surviving.
365. Conclusion
- 1. We should have a new recognition for the
insurance growth level of each country. - BRIP gives a different and probably more
reasonable answer - 2. The insurance growth in developed countries is
mainly driven by the economic factors, while that
in emerging countries is largely driven by the
institutional factors. - 3. As the economy develops, the contribution of
the institutional factors to the insurance growth
would gradually decrease, and the economic
factors would play a more active role in driving
the insurance growth.
37Thank you for your kind attention!Comments are
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